Mapping and measuring proteomes

Comunicaciones a congreso

Application of SWATH Proteomics to Mouse Biology.

The quantitative measurement of the proteome has been shown to yield new insights into physiology and cell biology that cannot be determined from the genome and transcriptome because the quantitative relationship between transcriptome and proteome is complex. MS-based proteomics techniques, such as SWATH-MS, have recently advanced to the point at which they may be reliably applied by biologists who are not specialists in mass spectrometry. Here we provide standard protocols for preparation of tissue samples for input into the SWATH-MS analytical pipeline. These protocols are designed for high-throughput processing of tissues with >/=5 mg of sample available for analysis. Studies with extremely limited amounts of tissue should consider PCT-SWATH. An experienced single user should be able to process 48 samples per day for injection into the mass spectrometer, or up to 144 samples a week. The machine time necessary for running these samples with SWATH is approximately 1.5 hr per sample. Data acquisition protocols are also provided. (c) 2017 by John Wiley & Sons, Inc

Xwalk: computing and visualizing distances in cross-linking experiments

Motivation: Chemical cross-linking of proteins or protein complexes and the mass spectrometry-based localization of the cross-linked amino acids in peptide sequences is a powerful method for generating distance restraints on the substrate's topology. Results: Here, we introduce the algorithm Xwalk for predicting and validating these cross-links on existing protein structures. Xwalk calculates and displays non-linear distances between chemically cross-linked amino acids on protein surfaces, while mimicking the flexibility and non-linearity of cross-linker molecules. It returns a ‘solvent accessible surface distance', which corresponds to the length of the shortest path between two amino acids, where the path leads through solvent occupied space without penetrating the protein surface. Availability: Xwalk is freely available as a web server or stand-alone JAVA application at http://www.xwalk.org. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

An Out-of-Core GPU based dimensionality reduction algorithm for Big Mass Spectrometry Data and its application in bottom-up Proteomics

Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra. Our proposed algorithm uses novel data structures which optimize the memory and computational operations inside GPU. These novel data structures include Binary Spectra and Quantized Indexed Spectra (QIS). The former helps in communicating essential information between CPU and GPU using minimum amount of data while latter enables us to store and process complex 3-D data structure into a 1-D array structure while maintaining the integrity of MS data. Our proposed algorithm also takes into account the limited memory of GPUs and switches between in-core and out-of-core modes based upon the size of input data. G-MSR achieves a peak speed-up of 386x over its sequential counterpart and is shown to process over a million spectra in just 32 seconds. The code for this algorithm is available as a GPL open-source at GitHub at the following link: https://github.com/pcdslab/G-MSR

Proteome coverage prediction with infinite Markov models

Motivation: Liquid chromatography tandem mass spectrometry (LC-MS/MS) is the predominant method to comprehensively characterize complex protein mixtures such as samples from prefractionated or complete proteomes. In order to maximize proteome coverage for the studied sample, i.e. identify as many traceable proteins as possible, LC-MS/MS experiments are typically repeated extensively and the results combined. Proteome coverage prediction is the task of estimating the number of peptide discoveries of future LC-MS/MS experiments. Proteome coverage prediction is important to enhance the design of efficient proteomics studies. To date, there does not exist any method to reliably estimate the increase of proteome coverage at an early stage. Results: We propose an extended infinite Markov model DiriSim to extrapolate the progression of proteome coverage based on a small number of already performed LC-MS/MS experiments. The method explicitly accounts for the uncertainty of peptide identifications. We tested DiriSim on a set of 37 LC-MS/MS experiments of a complete proteome sample and demonstrated that DiriSim correctly predicts the coverage progression already from a small subset of experiments. The predicted progression enabled us to specify maximal coverage for the test sample. We demonstrated that quality requirements on the final proteome map impose an upper bound on the number of useful experiment repetitions and limit the achievable proteome coverage. Contact: [email protected]; [email protected]

Electroblotting onto activated glass. High efficiency preparation of proteins from analytical sodium dodecyl sulfate-polyacrylamide gels for direct sequence analysis

We have developed a new method for the isolation of proteins for microsequencing. It consists of electrophoretic transfer (electroblotting) of proteins or their cleavage fragments onto activated glass filter paper sheets immediately after separation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The proteins are immobilized on the glass fiber sheets by ionic interactions or by covalent attachment. A wide range of proteins can be prepared in this fashion with no apparent restriction due to solubility, size, charge, or other intrinsic properties of the proteins. As little as 50 ng of the transferred proteins can be detected using Coomassie Blue or fluorescent dye staining procedures and even smaller amounts of radiolabeled proteins by autoradiography. After detection, the protein- containing bands or spots are cut out and inserted directly into a gas- phase sequenator. The piece of glass fiber sheet acts as a support for the protein during the sequencing. Amounts of protein in the 5- to 150- pmol range can be sequenced, and extended runs can be obtained from the blotted samples because of improved stepwise yields and lower backgrounds. The method has been successfully applied to the sequencing of a variety of proteins and peptides isolated from one-dimensional and two-dimensional polyacrylamide gels

Molecular architecture of human polycomb repressive complex 2.

Polycomb Repressive Complex 2 (PRC2) is essential for gene silencing, establishing transcriptional repression of specific genes by tri-methylating Lysine 27 of histone H3, a process mediated by cofactors such as AEBP2. In spite of its biological importance, little is known about PRC2 architecture and subunit organization. Here, we present the first three-dimensional electron microscopy structure of the human PRC2 complex bound to its cofactor AEBP2. Using a novel internal protein tagging-method, in combination with isotopic chemical cross-linking and mass spectrometry, we have localized all the PRC2 subunits and their functional domains and generated a detailed map of interactions. The position and stabilization effect of AEBP2 suggests an allosteric role of this cofactor in regulating gene silencing. Regions in PRC2 that interact with modified histone tails are localized near the methyltransferase site, suggesting a molecular mechanism for the chromatin-based regulation of PRC2 activity.DOI:http://dx.doi.org/10.7554/eLife.00005.001

Crosslinking-MS analysis reveals RNA polymerase I domain architecture and basis of rRNA cleavage

RNA polymerase (Pol) I contains a 10-subunit catalytic core that is related to the core of Pol II and includes subunit A12.2. In addition, Pol I contains the heterodimeric subcomplexes A14/43 and A49/34.5, which are related to the Pol II subcomplex Rpb4/7 and the Pol II initiation factor TFIIF, respectively. Here we used lysine-lysine crosslinking, mass spectrometry (MS) and modeling based on five crystal structures, to extend the previous homology model of the Pol I core, to confirm the location of A14/43 and to position A12.2 and A49/34.5 on the core. In the resulting model of Pol I, the C-terminal ribbon (C-ribbon) domain of A12.2 reaches the active site via the polymerase pore, like the C-ribbon of the Pol II cleavage factor TFIIS, explaining why the intrinsic RNA cleavage activity of Pol I is strong, in contrast to the weak cleavage activity of Pol II. The A49/34.5 dimerization module resides on the polymerase lobe, like TFIIF, whereas the A49 tWH domain resides above the cleft, resembling parts of TFIIE. This indicates that Pol I and also Pol III are distantly related to a Pol II-TFIIS-TFIIF-TFIIE comple

An integrated workflow for charting the human interaction proteome: insights into the PP2A system

Protein complexes represent major functional units for the execution of biological processes. Systematic affinity purification coupled with mass spectrometry (AP-MS) yielded a wealth of information on the compendium of protein complexes expressed in Saccharomyces cerevisiae. However, global AP-MS analysis of human protein complexes is hampered by the low throughput, sensitivity and data robustness of existing procedures, which limit its application for systems biology research. Here, we address these limitations by a novel integrated method, which we applied and benchmarked for the human protein phosphatase 2A system. We identified a total of 197 protein interactions with high reproducibility, showing the coexistence of distinct classes of phosphatase complexes that are linked to proteins implicated in mitosis, cell signalling, DNA damage control and more. These results show that the presented analytical process will substantially advance throughput and reproducibility in future systematic AP-MS studies on human protein complexes

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR

Motivation: Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. Results: We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. Availability and implementation: TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin